Uni- and multivariate bias adjustment methods in Nordic catchments: Complexity and performance in a changing climate br
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Uni- and multivariate bias adjustment methods in Nordic catchments : Complexity and performance in a changing climate br. / Tootoonchi, Faranak; Haerter, Jan O.; Todorovic, Andrijana; Raty, Olle; Grabs, Thomas; Teutschbein, Claudia.
I: Science of the Total Environment, Bind 853, 158615, 20.12.2022.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Uni- and multivariate bias adjustment methods in Nordic catchments
T2 - Complexity and performance in a changing climate br
AU - Tootoonchi, Faranak
AU - Haerter, Jan O.
AU - Todorovic, Andrijana
AU - Raty, Olle
AU - Grabs, Thomas
AU - Teutschbein, Claudia
PY - 2022/12/20
Y1 - 2022/12/20
N2 - For climate-change impact studies at the catchment scale, meteorological variables are typically extracted from ensem-ble simulations provided by global and regional climate models, which are then downscaled and bias-adjusted for eachstudy site. For bias adjustment, different statistical methods that re-scaleclimate model outputs have been suggested inthe scientific literature. They range from simple univariate methods that adjust each meteorological variable individ-ually, to more complex and more demanding multivariate methods that take existing relationships between meteoro-logical variables into consideration. Over the past decade, several attempts have been made to evaluate such methodsin various regions. There is, however, still no guidance for choosing appropriate bias adjustment methods for a study athand. In particular, the question whether the benefits of potentially improved adjustments outweigh the cost of in-creased complexity, remains unanswered.This paper presents a comprehensive evaluation of the performance of two commonly used univariate and two multi-variate bias adjustment methods in reproducing numerous univariate, multivariate and temporal features of precipita-tion and temperature series in different catchments in Sweden. The paper culminates in a discussion on trade-offs between the potential benefits (i.e., skills and added value) and disadvantages (complexity and computational de-mand) of each method to offer plausible, defensible and actionable insights from the standpoint of climate-change im-pact studies in high latitudes.We concluded that all selected bias adjustment methods generally improved the raw climate model simulations, but that not a single method consistently outperformed the other methods. There were, however, differences in the methods' performance for particular statistical features, indicating that other practical aspects such as computationaltime and heavy theoretical requirements should also be taken into consideration when choosing an appropriate biasadjustment method
AB - For climate-change impact studies at the catchment scale, meteorological variables are typically extracted from ensem-ble simulations provided by global and regional climate models, which are then downscaled and bias-adjusted for eachstudy site. For bias adjustment, different statistical methods that re-scaleclimate model outputs have been suggested inthe scientific literature. They range from simple univariate methods that adjust each meteorological variable individ-ually, to more complex and more demanding multivariate methods that take existing relationships between meteoro-logical variables into consideration. Over the past decade, several attempts have been made to evaluate such methodsin various regions. There is, however, still no guidance for choosing appropriate bias adjustment methods for a study athand. In particular, the question whether the benefits of potentially improved adjustments outweigh the cost of in-creased complexity, remains unanswered.This paper presents a comprehensive evaluation of the performance of two commonly used univariate and two multi-variate bias adjustment methods in reproducing numerous univariate, multivariate and temporal features of precipita-tion and temperature series in different catchments in Sweden. The paper culminates in a discussion on trade-offs between the potential benefits (i.e., skills and added value) and disadvantages (complexity and computational de-mand) of each method to offer plausible, defensible and actionable insights from the standpoint of climate-change im-pact studies in high latitudes.We concluded that all selected bias adjustment methods generally improved the raw climate model simulations, but that not a single method consistently outperformed the other methods. There were, however, differences in the methods' performance for particular statistical features, indicating that other practical aspects such as computationaltime and heavy theoretical requirements should also be taken into consideration when choosing an appropriate biasadjustment method
KW - Bias adjustment
KW - Bias correction
KW - Univariate and multivariate methods
KW - Precipitation and temperature
KW - Climate change
KW - Sweden
KW - SURFACE-TEMPERATURE
KW - CROSS-VALIDATION
KW - FUTURE CLIMATE
KW - PRECIPITATION
KW - SIMULATIONS
KW - MODEL
KW - IMPACT
KW - SCALE
KW - PROJECTIONS
KW - RISK
U2 - 10.1016/j.scitotenv.2022.158615
DO - 10.1016/j.scitotenv.2022.158615
M3 - Journal article
C2 - 36089026
VL - 853
JO - Science of the Total Environment
JF - Science of the Total Environment
SN - 0048-9697
M1 - 158615
ER -
ID: 322567471